Computational Methods for the Innovative Design of Electrical Devices [electronic resource] /
Wiak, Slawomir.editor.
Napieralska Juszczak, Ewa.editor.
Computational Methods for the Innovative Design of Electrical Devices is entirely focused on the optimal design of various classes of electrical devices. Emerging new methods, like e.g. those based on genetic algorithms, are presented and applied in the design optimization of different devices and systems. Accordingly, the solution to field analysis problems is based on the use of finite element method, and analytical methods as well. An original aspect of the book is the broad spectrum of applications in the area of electrical engineering, especially electrical machines. This way, traditional design criteria of conventional devices are revisited in a critical way, and some innovative solutions are suggested. In particular, the optimization procedures developed are oriented to three main aspects: shape design, material properties identification, machine optimal behaviour. Topics covered include: • New parallel finite-element solvers • Response surface method • Evolutionary computing • Multiobjective optimization • Swarm intelligence • MEMS applications • Identification of magnetic properties of anisotropic laminations • Neural networks for non-destructive testing • Brushless DC motors, transformers • Permanent magnet disc motors, magnetic separators • Magnetic levitation systems.
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references.
Integrated Computer Models of 3-D Comb Drive Electrostatic MEMS Structures .-Multiobjective Design Optimization of Slotless PM Motors Using Genetic -- Algorithms based on Analytical Field Calculation -- The FEM parallel simulation with look up tables applied to the brushless DC motor optimization -- Fast algorithms for the design of complex-shape devices in electromechanics -- Optimization of Wound Rotor Synchronous Generators based on Genetic Algorithms -- Simple and Fast Algorithms for the Optimal Design of Complex Electrical Machines.-The flock of starlings optimization: influence of topological rules on the collective behavior of swarm intelligence -- Multilevel Data Classification and Function Approximation Using Hierarchical Neural Networks -- Parametric identification of a three-phase machine with genetic algorithms -- Ridge Polynomial Neural Network for Non-Destructive Eddy Current Evaluation -- Structural-Systematic Approach in Magnetic Separators Design -- Weight Reduction of Electromagnet in Magnetic Levitation System for Contactless Delivery Application -- Genetic algorithm algorithm applied in optimal design of PM disc motor using specific power as objective -- Magnetically Nonlinear Iron Core Characteristics of Transformers Determined by Differential Evolution -- Different Methods for Computational Electromagnetics: their Characteristics and Typical Practical Applications.-Methods of homogenization of laminated structures.-Application examples.
Computational Methods for the Innovative Design of Electrical Devices is entirely focused on the optimal design of various classes of electrical devices. Emerging new methods, like e.g. those based on genetic algorithms, are presented and applied in the design optimization of different devices and systems. Accordingly, the solution to field analysis problems is based on the use of finite element method, and analytical methods as well. An original aspect of the book is the broad spectrum of applications in the area of electrical engineering, especially electrical machines. This way, traditional design criteria of conventional devices are revisited in a critical way, and some innovative solutions are suggested. In particular, the optimization procedures developed are oriented to three main aspects: shape design, material properties identification, machine optimal behaviour. Topics covered include: • New parallel finite-element solvers • Response surface method • Evolutionary computing • Multiobjective optimization • Swarm intelligence • MEMS applications • Identification of magnetic properties of anisotropic laminations • Neural networks for non-destructive testing • Brushless DC motors, transformers • Permanent magnet disc motors, magnetic separators • Magnetic levitation systems.
Computational intelligence.
Artificial intelligence.
Electrical engineering.
Computational Intelligence.
Artificial Intelligence.
Electrical Engineering.
Studies in Computational Intelligence